Potential of Wind Energy Development for Water Pumping in Ngaoundere

Mouangue, Ruben; Kazet, Myrin Y.; Lissouck, Daniel; Kuitche, Alexis; Ndjaka, J.M.B.

doi:10.4172/2090-4541.1000198

Cited by 2 publications

(2 citation statements)

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“…These losses are linked to the geometry of the wind farm, to the wind statistics (with great importance of the direction), and to the power curve of the wind turbines. (15) The other losses or loss factors are linked to the production activity and are systematically estimated by standard error percentages. (16) Gross production adjusted for wake effects is applied to the wake model and estimated production losses.…”

Section: Methodsmentioning

confidence: 99%

“…The authors concluded, based on these results and discussions, that the best wind turbines at the Elkharga site can be ranked in decent order as V162, V150, and V110. Although there are a number of studies in the open literature that have discussed the wind potential of certain (regions) areas in Cameroon [1][2][3][4][5][6][7][8][14][15][16][17][18][19], as these studies have shown different results, the determination, modification, proposal, and development of optimal and optimized methods for technoeconomic assessments of wind potential and the cost of energy produced are continuing. However, a technoeconomic analysis combined with the development of wind resource maps, in the occurrence of maps of wind speed, energy produced, and cost of production generated using GIS software (geographic information system) by following an applied geographic approach, is necessary.…”

Section: Introductionmentioning

confidence: 99%

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Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

Koung,

Menga,

Bonoma

et al. 2024

International Journal of Energy Research

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This paper performs a technoeconomic analysis of the wind power potential and evaluates the cost of wind power generation in Evodoula, comparing two methods, the conventional method and the uncertainty method based on a comparative spatiotemporal approach using the geographic information system (GIS) software tool. This study is based on satellite wind data measured at 10 m above ground level (AGL) over a 40-year period (1980-2019), by the meteorological service NASA (National Aeronautics and Space Administration)/Goddard Space Flight Center (GSFC). The main objectives are to obtain an appropriate design for a proven optimal location and to assess the viability of wind power at Evodoula. For this type of study, there is little literature available. The optimization of an onshore wind farm and deployment in the wind energy development interest area (ZIDEE) is carried out to obtain a minimum and parsimonious discounted cost production unitary (CPU) of the electricity produced. The results showed that in Okok, a location with a large energy deficit, an onshore wind farm with an electricity generation capacity of 12.5 MW with 5 NORDEX N100-2.5MW wind turbines would have a total energy production (TEP) of about 64.0254825 TWh and a selling price of electricity that would be 0.0034 CAD$/kWh, which is very low compared to the utility price (about 98% cheaper). The total cost of the wind farm would be about $11 million, with a net present cost of about $218 million. The annual profit generated by the wind farm would be over $6 billion. The return on investment (ROI) of the project is estimated at 2880.882%. The constructed onshore wind farm would avoid CO2 emission at over 11 MtCO2,eq/year as the energy generated is from the atmosphere. The wind farm would realize an average annual cash flow estimated at nearly $30 million after 20 years of operation. These savings would allow the installation of CO2 capture systems in conventional power plants. In addition, the analysis of uncertainties and risks was identified and quantified to estimate the confidence levels of the project development results. The risks have been assessed, and we recommend that the total uncertainty of the project is around 15%. The energy values in P75 and P90 are 10.08% and 19.22%, respectively, lower than the energy value in P50 of 11.60 GWh/An. Finally, the main policy recommendations for an inclusive design process are highlighted. The contribution of this study is to assist policy makers in making appropriate decisions in the development and implementation of energy and environmental policy in Cameroon and in many continental areas.

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Section: Methodsmentioning

confidence: 99%